“We are moving slowly into an era where big data is the starting point, not the end.” – Pearl Zhu, author of the “Digital Master” book series.
I have spoken a lot about data driven decision making within an organisation. In order to be in a position where data is centric to an organisation's decision-making process, there are a series of elaborate steps needed to become a mature data driven organisation. From data strategy, democratisation of data to eventually data visualisation.
Today I want to talk about the importance of data democratisation and how making this centric helps drive the maturity of an organisation’s data journey.
So, what is data democratisation?
Data democratisation is enabling all business users to have access to the organisation's data and therefore derive meaningful insights to drive decision making. The ultimate goal of data democratisation is about easy and meaningful access to the data an organisation captures, where there is no gatekeeper that creates a bottleneck at the gateway to the data.
A few years back, data was "owned" by the IT gatekeepers and whenever management wanted to see a certain type of information, the data analysts would extract that information and provide it to them. So, I hear you say, what is wrong it that? As organisations started to become inundated with data, accessing that data became a problem. Ease of access and having data at one’s fingertips to make decisions became a problem. Data democratisation removes that bottleneck and frustration.
Considerations when democratising data:
To build a robust data democratisation process one needs to make sure an organisation has at least the following in place:
Data governance - Making sure that different teams have a standard way of accessing the data. Risks around data visibility and security consideration needs to be carefully planned. With greater accessibility risk around data security increases, so it is important to put safeguards and rules in place which are clearly laid out for cross functional teams.
Reducing Silos - Democratisation comes into play to reduce data silos but often, when not properly implemented, it creates more fragmented silos. Data democratisation should consider information needed at all levels, e.g. a marketing manager might want to see the success of a particular marketing campaign whereas a CMO might want to see the ROI of that campaign. Having data that gives both the manager and CMO easy access to that information is critically important in the data democratisation process.
Training - Teams must be taken through proper training to remove fears surrounding misrepresentation of data and how to use it to achieve organisational goals. Teams should also be trained in the standard software that would help them to gain insights from that data.
Any organisation embarking on a data democratisation programme must involve one member from different departments as their task force. Most Data democratisation programmes fail because of trust. When individuals across the whole organisation is empowered with enhanced decision-making capability with access to unfettered data, it is of utmost importance to make sure the quality of that data is thoroughly reviewed. Any data project will lack credibility if the output is rife with data quality issues.
Data democratisation programs need to think about scalability, data is growing at a tremendous rate. IDC predicts that the collective sum of the world's data will grow from 33 zettabytes this year to a 175ZB by 2025, for a compounded annual growth rate of 61 percent. Investing in a data democratisation programme should consider the data growth of that organisation.
Data Management – Processes should be put in place to make sure that response times of failed data collection and transformation do not impact the end users. Choosing the right vendor is a serious component to factor in when embarking on data democracy projects. Trust in vendors that can handle known pitfalls or potential glitches. Vendors that can highlight concerns even before they become an issue. Vendors should be able to resolve failures easily, be responsive and more importantly understand the culture and business of the organisation. Trust on the whole programme relies on how efficiently, and responsively the whole process of data collection, transformation and presentation is made available to the end users.
Technological stack, especially BI tools, which will empower users with enhanced decision-making powers should be thoroughly accessed. Workshops with the task force, their concerns and wishes should be thoroughly handheld to build a transformational culture. Data Dictionary should be laid out in simple business terms and should be consistent across all sources of data.
In a 2019 Big Data and AI Executive Survey by NewVantage Partners, executives from corporations such as American Express, Ford, General Electric, and Johnson & Johnson admitted they weren’t where they wanted to be on the road to data democratization.
Data democratisation is a game changer for any organisation that implements it well. Done rightfully and carefully, enables all teams to put data in the centre of decision making in a seamless manner thereby giving a competitive advantage and increasing bottom line massively.
About the Author: Sarbani is the Managing Director of ei²® a consultancy specialising in #data #insights #performance